Real-time modelling with EpiNow2
Example applications

Sebastian Funk (@sbfnk)
https://epiforecasts.io

12 December, 2022
100 days and 100 lines of code

“We were losing ourselves in details […] all we needed to know is, are the number of cases rising, falling or levelling off?”

Hans Rosling, Liberia, 2014

Infections are reported with a delay

Data contain noise and reporting artefacts

Epidemics grow exponentially

EpiNow2

An R package for situational assessment in outbreaks taking into account

reporting delays and truncation
reporting artefacts such as week-day effects
exponential nature of epidemics

EpiNow2

and many contributions from people that don’t show up in code

EpiNow2

https://epiforecasts.io/EpiNow2
Abbott et al., Wellcome Open Res, 2020

Application: COVID-19

https://epiforecasts.io/covid
https://epiforecasts.io/posts/2022-03-25-rt-reflections

Application: Monkeypox nowcasting

https://github.com/epiforecasts/nowcasting.example

Application: Cholera in Haiti

Future development: flexible nowcasting

https://package.epinowcast.org/dev/

Outbreak modelling has common tasks
Methods usually chosen for availability
Much scope for improving
- software,
- methodology and
- practices